Cloud computing has emerged as a new technology across organization and cooperates that impacts several different research fields, including software testing. To provide a cloud service and sharing resources successfully, the cloud must be tested before it comes into offering services. Testing the applications has their own testing tools and testing methodologies. In this paper we provide an overview regarding cloud computing trends, types, challenges, tools and the comparison of tools for cloud testing.

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Knowledge Management System (KMS) is a collective process of organizational knowledge from capturing to dissemination. The three fourth of world’s corporate market value resides today in assets such as intellectual property, customer data, financial records, strategies and trade secrets. These assets are all knowledge based. KMS becomes inexorable to achieve competitive advantages in this present information and communication technology epoch. However Lack of effectiveness in knowledge Management System is turmoil to any organization due to its integrated domain. But an effective KMS can helps to organization to achieve tremendous benefits such as competitive advantages, innovation, leadership, social values, increased customer satisfactions, quality in product, financial credibility and people values, So knowledge management system needs to consider significant views such as technical, functional, people and organization image for effectiveness. Almost all the research works related to quality model for KMS are limited in views. This paper proposes an effectiveness framework which includes significant quality dimensions and variables to measure each. This paper also includes empirical validation using data collected from three sectors: nuclear power production, Electrical equipment manufacturing and software industry for suitability analysis through statistical method. We considered primary variable from each identified dimension to analyze the suitability of KMS with 25 knowledge workers in each sector through five parameters: Completeness of product, Customization of process, Ontology standard, Applicability of KMS content, and Decision making ability.

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